SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8051–8075 of 10420 papers

TitleStatusHype
A Multi-stage Transfer Learning Framework for Diabetic Retinopathy Grading on Small Data—0
A fast dynamic graph convolutional network and CNN parallel network for hyperspectral image classification—0
Few-Shot Learning Approach on Tuberculosis Classification Based on Chest X-Ray Images—0
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward—0
Feature Whitening via Gradient Transformation for Improved Convergence—0
Rethinking the Zigzag Flattening for Image Reading—0
Rethinking Two Consensuses of the Transferability in Deep Learning—0
Unauthorized AI cannot Recognize Me: Reversible Adversarial Example—0
Few-shot Image Classification with Multi-Facet Prototypes—0
Few-Shot Image Classification via Contrastive Self-Supervised Learning—0
A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification—0
Foveated Retinotopy Improves Classification and Localization in CNNs—0
Compute Less to Get More: Using ORC to Improve Sparse Filtering—0
A Fistful of Words: Learning Transferable Visual Models from Bag-of-Words Supervision—0
Few-shot Image Classification based on Gradual Machine Learning—0
Few-Shot Image Classification and Segmentation as Visual Question Answering Using Vision-Language Models—0
Compute-Efficient Medical Image Classification with Softmax-Free Transformers and Sequence Normalization—0
Few-Shot Image Classification Along Sparse Graphs—0
Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning—0
Computed tomography using meta-optics—0
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs—0
FedDiff: Diffusion Model Driven Federated Learning for Multi-Modal and Multi-Clients—0
Reversed Active Learning based Atrous DenseNet for Pathological Image Classification—0
Reverse engineering adversarial attacks with fingerprints from adversarial examples—0
LAM3D: Leveraging Attention for Monocular 3D Object Detection—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified